Three Drafts of the Same House
The three levels every data model passes through — conceptual, logical, and physical — and how AI is starting to help draft each one faster.
Part 2
Part 3
Who's Related to Whom
How entity-relationship modelling works — entities, attributes, and relationship types — through the familiar lens of a family tree, and how AI is changing the way relationships get discovered.
Part 4
A Pantry That Makes Sense
What normalization (and denormalization) actually mean, why duplicated data quietly causes inconsistency, and how AI is changing how that duplication gets found.
Part 5
Designing the Store Floor
How dimensional modelling (star and snowflake schemas) organizes data around how people ask questions, not just how it's stored — and how AI is changing who's "walking the store."
Part 6
The Library and the Storage Unit
The difference between modelling for a data warehouse versus a data lake — structure-first versus store-first approaches — and how AI is starting to act as an on-demand librarian for the more flexible option.
Part 7
Renovating a House With People Still Inside
How schema evolution and versioning let a data model change safely over time without breaking everything downstream — and how AI is making it safer to swing the hammer.
Part 8
An Apprentice Who Drafts While You Decide
What AI-assisted and automated data modelling tools actually do today, and why the human architect's judgment still matters as much as ever.
Part 9
A Tour Guide for the City's Data
What semantic layers and knowledge graphs add on top of a data model, and why AI tools are only as trustworthy as the shared meaning they're given.
Part 10
The City, Reassembled
How every concept from this series fits together as one AI-ready city, and where data modelling's evolving relationship with AI is likely headed next.